Add PROTEUS module diagram

docs/Explanations/authoritative_oxygen.md

@@ -83,7 +83,7 @@ A `random_seed` argument (default `None`) seeds a `np.random.default_rng` for th
 
 ## Buffer convention
 
-Like the buffered mode, the authoritative-O mode references $f_{\mathrm{O}_2}$ to the iron-wüstite buffer of O'Neill & Eggins (2002)[^cite-oneilleggins2002] by default, with the Fischer et al. (2011)[^cite-fischer2011] alternative selectable through `OxygenFugacity()` instantiation. The returned `fO2_shift_derived` is the $\Delta\mathrm{IW}$ relative to whichever buffer was chosen.
+Like the buffered mode, the authoritative-O mode references $f_{\mathrm{O}_2}$ to the iron-wüstite buffer of O'Neill & Eggins (2002) [^cite-oneilleggins2002] by default, with the Fischer et al. (2011) [^cite-fischer2011] alternative selectable through `OxygenFugacity()` instantiation. The returned `fO2_shift_derived` is the $\Delta\mathrm{IW}$ relative to whichever buffer was chosen.
 
 !!! note "Cross-backend buffer divergence"
     PROTEUS supports a second outgassing backend, [atmodeller](https://atmodeller.readthedocs.io/), whose authoritative-O implementation uses the Hirschmann combined IW buffer. The Hirschmann and O'Neill & Eggins parameterisations differ by ${\sim}0.95$ dex at $T = 3000$ K. PROTEUS records both backends' derived offsets under the helpfile column `fO2_shift_IW_derived`, and the discrepancy is documented in the column's schema comment. The two backends agree on the underlying physics (same chemistry of FeO-O$_2$ equilibrium); they disagree on the numerical parameterisation of the buffer curve. Choose one backend per run and stay with it for any cross-time-step comparison.
@@ -113,5 +113,5 @@ For the routine "set $\Delta\mathrm{IW}$, get a self-consistent atmosphere" work
 - [Coupling to PROTEUS (theory)](proteus_coupling.md): how the PROTEUS wrapper selects between the two modes.
 - [API reference for `calliope.solve`](../Reference/api/calliope.solve.md).
 
-[^cite-oneilleggins2002]: H. St. C. O'Neill, S. M. Eggins, *[The effect of melt composition on trace element partitioning: an experimental investigation of the activity coefficients of FeO, NiO, CoO, MoO$_2$ and MoO$_3$ in silicate melts](https://doi.org/10.1016/S0009-2541(01)00414-4)*, Chemical Geology, 186, 151–181, 2002. [SciX](https://scixplorer.org/abs/2002ChGeo.186..151O/abstract).
-[^cite-fischer2011]: R. A. Fischer, A. J. Campbell, G. A. Shofner, O. T. Lord, P. Dera, V. B. Prakapenka, *[Equation of state and phase diagram of FeO](https://doi.org/10.1016/j.epsl.2011.02.025)*, Earth and Planetary Science Letters, 304, 496–502, 2011. [SciX](https://scixplorer.org/abs/2011E%26PSL.304..496F/abstract).
+ [^cite-oneilleggins2002]: H. St. C. O'Neill, S. M. Eggins, *[The effect of melt composition on trace element partitioning: an experimental investigation of the activity coefficients of FeO, NiO, CoO, MoO$_2$ and MoO$_3$ in silicate melts](https://doi.org/10.1016/S0009-2541(01)00414-4)*, Chemical Geology, 186, 151–181, 2002. [SciX](https://scixplorer.org/abs/2002ChGeo.186..151O/abstract).
+ [^cite-fischer2011]: R. A. Fischer, A. J. Campbell, G. A. Shofner, O. T. Lord, P. Dera, V. B. Prakapenka, *[Equation of state and phase diagram of FeO](https://doi.org/10.1016/j.epsl.2011.02.025)*, Earth and Planetary Science Letters, 304, 496–502, 2011. [SciX](https://scixplorer.org/abs/2011E%26PSL.304..496F/abstract).

docs/Explanations/code_architecture.md

@@ -65,7 +65,7 @@ The orchestration layer. Two solver entry points, the buffered mode and the auth
 Plus seven shared helpers:
 
 - `get_partial_pressures(pin, ddict)`: walks the eleven-species speciation tree from the four primary pressures.
-- `atmosphere_mass(pin, ddict)`: applies Bower et al. (2019)[^cite-bower2019] Eq. 2 to every species and aggregates atomic-mass tallies per element.
+- `atmosphere_mass(pin, ddict)`: applies Bower et al. (2019) [^cite-bower2019] Eq. 2 to every species and aggregates atomic-mass tallies per element.
 - `dissolved_mass(pin, ddict)`: applies the chosen solubility law for each soluble species and aggregates atomic-mass tallies per element.
 - `get_target_from_params(ddict)`: translates `hydrogen_earth_oceans`, `CH_ratio`, `nitrogen_ppmw`, `sulfur_ppmw` into kg-per-element targets (four-key, for the buffered mode).
 - `get_target_from_pressures(ddict)`: back-computes kg-per-element targets from prescribed initial atmospheric pressures.
@@ -140,4 +140,4 @@ For batch use cases (sensitivity sweeps, parameter studies), wrap a Python loop
 - [API reference](../Reference/api/index.md) for the auto-generated per-symbol documentation.
 - [Source on GitHub](https://github.com/FormingWorlds/CALLIOPE/tree/main/src/calliope) for the actual implementation.
 
-[^cite-bower2019]: D. J. Bower, D. Kitzmann, A. S. Wolf, P. Sanan, C. Dorn, A. V. Oza, *[Linking the evolution of terrestrial interiors and an early outgassed atmosphere to astrophysical observations](https://doi.org/10.1051/0004-6361/201935710)*, Astronomy & Astrophysics, 631, A103, 2019. [SciX](https://scixplorer.org/abs/2019A%26A...631A.103B/abstract).
+ [^cite-bower2019]: D. J. Bower, D. Kitzmann, A. S. Wolf, P. Sanan, C. Dorn, A. V. Oza, *[Linking the evolution of terrestrial interiors and an early outgassed atmosphere to astrophysical observations](https://doi.org/10.1051/0004-6361/201935710)*, Astronomy & Astrophysics, 631, A103, 2019. [SciX](https://scixplorer.org/abs/2019A%26A...631A.103B/abstract).